Prevalence, cessation, and geographical variation of smoking among middle-aged and elderly adults in China: A population-based study

INTRODUCTION Smoking significantly burdens human health, contributing to an increasing incidence of mortality and morbidity. This study aims to explore the prevalence of smoking, cessation, and the association between various risk factors and smoking intensity measured in pack-years among Chinese adults. METHODS During 2020–2021, the China Stroke High-risk Population Screening and Intervention Program (CSHPSIP) invited participants aged ≥40 years from 31 provinces in mainland China. This cross-sectional study presents the standardized prevalence of smoking and cessation across various demographics, including age, sex, residence, income, education level, BMI, and geographical region of residence. Multivariable logistic regression was used to examine the associations between smoking pack-years and related factors. RESULTS Among 524741 participants (mean age: 61.9 ± 10.9 years; 41.1% male; 58.9% female), standardized smoking prevalence was 19.3% (95% CI: 19.2–19.4), with men (37.2%; 95% CI: 37.0–37.4) displaying significantly higher rates than women (1.3%; 95% CI: 1.2–1.3). Smoking cessation rate stood at 11.2% (95% CI: 11.0–11.4), with 11.3% (95% CI: 11.1–11.5) for men and 8.4% (95% CI: 7.5–9.2) for women. Urban residents and those with advanced education had lower smoking rates and higher cessation rates. Additionally, the dose-response relationship indicated a more pronounced association between higher smoking pack-years and elevated health risks, including hypertension (AOR=1.30; 95% CI: 1.24–1.36), diabetes (AOR=1.26; 95% CI: 1.20–1.33), hyperlipidemia (AOR=1.22; 95% CI: 1.16–1.28), heart disease (AOR=1.40; 95% CI: 1.26–1.54), and stroke (AOR=1.23; 95% CI: 1.10–1.36). CONCLUSIONS This comprehensive study emphasizes the profound impact of smoking on health in Chinese adults, indicating the critical need for tailored cessation programs, particularly for middle-aged individuals, men, rural residents, and those with lower level of education.


INTRODUCTION
Smoking represents a critical health hazard, significantly impacting human life and the global economy.Over the past three decades, smoking-related causes have resulted in >200 million deaths and an annual economic loss >1 trillion US dollars 1,2 .China alone has approximately 300 million smokers, accounting for nearly 40% of the world's total tobacco consumption, and the number of deaths caused by smoking in China is the highest in the world 3 .Projections indicate studies on smoking conditions among the entire population.To bridge this evidence gap, we examined data from the China Stroke High-risk Population Screening and Intervention Program (CSHPSIP) 2020-2021, a large-scale survey with national representation.This study aims to assess the prevalence of smoking and its cessation, and associations with sociodemographic factors among Chinese adults aged ≥40 years and encompassing specific subgroups.

Study design and study participants
We conducted a nationwide cross-sectional study in 2021, collecting data from December 2020 to December 2021.Detailed information about the design, objectives, and survey methods of CSHPSIP is available in a previous publication 15 .The study's methodology conformed to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines 16 .The Bigdata Observatory Platform for Stroke of China (BOSC) is a comprehensive reporting system that records details of individuals aged ≥40 years from every hospital admission throughout China 17 .Covering 31 provinces, autonomous regions, and municipalities across China, this study invited community residents (those residing at the current location for six months or longer) registered at participating hospitals and screening sites to take part.The study protocol received approval from the Ethics Committee of Capital Medical University's Xuanwu Hospital, in compliance with the Declaration of Helsinki (Reference No. 2012045).A detailed sampling design is described in Supplementary file Part 1.
After removing 4112 participants due to followup loss and 3093 due to deaths, the final number of individuals in our study was 525048 (Figure 1).Participants who had died were excluded because their deaths could confound the primary outcomes of interest related to smoking intensity and associated risk factors.The participants were divided into three groups: never smokers (N=445866), former smokers (N=11452), and current smokers (N=67730).

Diagnostic criteria
Current smokers were identified as those who were smoking at the time of the survey, while former smokers were those who had quit smoking by the time of the survey.Both former and current smokers were collectively referred to as ever smokers.We determined the smoking prevalence by dividing the number of ever smokers by the total study population.The smoking cessation rate was calculated as the ratio of former to ever smokers.Additionally, current smokers provided details about the smoking duration, from the year they began smoking to the present, and the total number of cigarettes smoked daily.To quantify cumulative smoking exposure, we calculated pack-years, a metric commonly used in smoking-related research.Pack-years were calculated by dividing the daily number of cigarettes by twenty (average cigarettes per pack), then multiplying by the total years the person has smoked 18 .

Covariates
Various sociodemographic factors were evaluated, including age, body mass index (BMI, kg/ m 2 ), education level, annual income level, and geographical region of residence.Age at the time of recruitment was treated as a continuous variable and additionally grouped into five age ranges: 40-49, 50-59, 60-69, 70-79, and ≥80 years.Hence, age was handled as a continuous and categorical variable.The education level was categorized as primary school or lower, middle school, high school, college or higher.Annual income was classified into four groups in RMB (1000 Chinese Renminbi about US$140): <5000, 5000-9999, 10000-19999, and ≥20000.Geographical regions were defined as follows: Northeast (Liaoning, Jilin, Heilongjiang), North (Beijing, Tianjin, Hebei, Shanxi, Inner Mongolia), Northwest (Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang), Southwest (Chongqing, Sichuan, Guizhou, Yunnan, Tibet), South (Guangdong, Guangxi, Hainan), Central (Henan, Hubei, Hunan), and East (Shanghai, Jiangsu, Zhejiang, Anhui, Fujian, Jiangxi, Shandong).Additionally, the study examined a range of factors associated with health outcomes, including hypertension, diabetes mellitus, hyperlipidemia, obesity, transient ischemic attack (TIA), alcohol consumption, heart disease, stroke, and associated laboratory tests.Trained physicians diagnosed these conditions through clinical examinations, medical history assessments, and laboratory test results.All measurements of associated factors are described in Supplementary file Part 2.

Statistical analysis
We assessed the characteristics of participants stratified by smoking status (never smokers, current smokers, and former smokers).Continuous variables were represented using means and standard deviations (SDs), and categorical variables were expressed in frequencies and percentages (%).The characteristics of the study population were compared using the Student's t-test for continuous variables and the chi-squared test for categorical ones.The study applied sex-and age-standardized prevalence that was adjusted to align with the national demographic profile.This adjustment involved using various sampling weights, including those for the study's design, the lack of response from some participants, and post-stratification (Supplementary file Part 3).
We applied multivariable logistic regression to calculate the odds ratios (ORs) and their 95% confidence intervals (95% CIs) for associations between smoking pack-years and various risk factors among current smokers, including hypertension, diabetes, hyperlipidemia, obesity, transient ischemic attack (TIA), heart disease, and stroke.Current smokers were stratified into three categories based on their pack-years: light smokers (1-20 pack-years), moderate smokers (21-40 pack-years), and heavy smokers (≥40 pack-years).To improve the accuracy of our findings, we adjusted for multiple potential confounders that could affect the relationships between smoking and these health conditions.Furthermore, we conducted subgroup analyses to explore the dose-response relationship between smoking pack-years and major health factors across different demographics, including age groups (middle-aged individuals, 40≤ and <60 years; and elders, aged ≥60 years), and genders (male, female).
Statistical analyses were conducted using SAS 9.4 and Python (version 3.9.12).All presented p-values were two-sided, with significance set at p<0.05.

Characteristics of participants
Among the 525048 participants aged ≥40 years, the average age was 61.9 years (SD=10.9).The vast majority (84.9%) were non-smokers, 12.9% were current smokers, and the remaining 2.2% were former smokers.Notably, the average age of former smokers was slightly higher at 66.0 years (SD=9.9).Furthermore, individuals who had never smoked or were former smokers were more likely to have a level of education of college or higher.Non-smokers generally had lower income levels compared to current and former smokers.Specifically, non-smokers had a higher proportion of individuals with an annual income of 0-5000 RMB compared to current and former smokers.In comparison, the proportion of non-smokers with an annual income of ≥20000 RMB was lower than that of current and former smokers.Almost all associated health factors were highest among former and, in some cases, among current smokers.Additionally, current and former smokers exhibited higher levels of systolic blood pressure (SBP), diastolic blood pressure (DBP), and homocysteine compared to non-smokers (Table 1).
Conversely, increased income correlated with reduced cessation rates.Interestingly, both the highly  The standardized prevalence was calculated using sampling weights that were multiplied by design, non-response, and poststratification weights.Poststratification weights were adjusted for residence, geographical location, sex, and age using the 2010 China census data.RMB: 1000 Chinese Renminbi about US$140.
Subgroup analysis, stratified by gender and age, examined the relationship between risk factors and pack-years, as detailed in Table 5.For males, the dose-response relationship was consistent with the overall population trends.Females faced increased heart disease and stroke risks with higher pack-years, most notably for those with >40 pack-years.Notably, females with greater than 40 pack-years also faced increased risks for hypertension and diabetes, a trend not observed in the 21-40 pack-year group compared to the reference category of 1-20 pack-years.In the cohort of younger participants (<60 years), higher pack-years was correlated with a considerable rise in the risk of hypertension, diabetes, hyperlipidemia, and heart disease.Conversely, for those aged ≥60 years, the risk increase was more modest, with only hyperlipidemia  showing a marked rise in the two higher pack-year groups and diabetes in the highest pack-year group.Obesity risk was greater in participants aged <60 years who smoked more than 40 pack-years but lower in those aged >60 years who smoked 21-40 pack-years, compared to the 1-20 pack-year reference group..Comparable smoking prevalence rates were recorded in other Asian countries, such as Thailand (20.7%) and South Korea (20.8%) 21,22 .However, in comparison to developed nations like the United Kingdom (12.9%) and the United States (11.5%), the smoking rate we observed was notably higher 23,24 .Such discrepancies might arise from variations in tobacco control programs and legislative measures in these nations.The study indicates that smoking rates in China are significantly higher among men compared to women, a disparity much larger than the gender gap observed in Europe 25 .This difference reflects the cultural acceptance in East Asia, where smoking is more socially acceptable for men than for women 26 .In our study, the smoking cessation rate was 11.2%.Compared to other regions, we noted that the smoking cessation rate in our study was slightly lower than in the United Kingdom 27 (14.0%)and Japan 28 (15.3%).Various factors motivate smokers to quit.Policies and legislation that enforce the prohibition of smoking in public places play a significant role in encouraging cessation.Further, the accessibility of diverse cessation aids, including counseling services, nicotine replacement therapies, and support groups, offers invaluable assistance in the quitting journey 29 .

DISCUSSION
To examine the relationship between social demographics and both smoking habits and cessation, factors such as education level, culture, and economic development may be influential 30 .Urban residents and individuals with higher level of education tend to smoke less and have higher cessation rates, consistent with the research of Meza et al. 31 .This trend is likely driven by greater health awareness and health consciousness among educated populations.Moreover, urban areas generally benefit from better infrastructure and healthcare facilities and are often the focus of health awareness campaigns, including smoking prohibition initiatives.Participants in South China had a lower smoking rate and a higher cessation rate, likely due to their higher socio-economic status, which leads to better health awareness, education, and access to smoking cessation resources 32 .Regions like Beijing demonstrate the impact of stringent tobacco control policies.The lower prevalence of smoking in these areas underscores the effectiveness of robust public health policies, comprehensive awareness campaigns, and strategic public health investments.
Additionally, the data indicate an increased likelihood of smoking cessation with advancing age, consistent with the result of Najafipour et al. 33 .When smokers recognize the adverse health effects of smoking, they may become more motivated to quit.This presents an ideal opportunity for doctors and family members to encourage smoking cessation, particularly in patients suffering from smokingrelated diseases.
Our results also indicate that smoking more than 40 pack-years substantially increases the risk of developing serious health conditions such as hypertension, diabetes, hyperlipidemia, heart disease, and stroke.The adverse effects of chronic tobacco smoking on blood pressure can be attributed to nicotine and carbon monoxide, two primary compounds found in tobacco.Nicotine causes both vasoconstriction and vasoparalytic effects, while chronic exposure to carbon monoxide can lead to irreversible changes in blood vessels 18 .Moreover, a Korean study demonstrated a dose-dependent effect of smoking on diabetes risk that persists even after cessation in those with over 14 pack-years of exposure, suggesting that the detrimental impacts of smoking on glucose metabolism are long-lasting and possibly irreversible 34 .Shah et al. 35 also found that extensive smoking history significantly elevates blood lipid levels, aligning with our findings.These physiological changes, aggregated over years of smoking, heighten the risk of disease, rendering longterm smokers particularly susceptible to severe health outcomes.

Strengths and limitations
Our study has several strengths, including a large and nationally representative sample size, well-validated questionnaires, and a rigorous quality control process.We collected a comprehensive range of data variables, encompassing smoking status, pack-years, demographic characteristics, and health conditions.This allowed for a deep understanding of the relationship between smoking and health outcomes.To strengthen the reliability of our results, we controlled for a variety of potential confounders, such as age, sex, BMI, and income.Our findings highlight a dose-response correlation between smoking severity and conditions such as hypertension, diabetes, hyperlipidemia, heart disease, and stroke.These insights emphasize the severe health repercussions of smoking habits and can guide the formulation of more effective preventative and control measures.Moreover, the risks associated with smoking are not uniform across gender or age groups, highlighting the need for targeted public health interventions and smoking cessation programs.
However, certain limitations should be considered when interpreting our findings.First, due to our study's cross-sectional design, there exists a potential for reverse causality; thus, our data reveals associations, not necessarily causative links.Longitudinal studies would be needed to address this concern.Second, the reliance on self-reported smoking status, without biochemical validation, might introduce biases such as recall and social desirability, potentially affecting the accuracy of smoking reports.Third, while we have accounted for various factors, we may have overlooked crucial determinants like age at smoking initiation, attempting and motivation to quit, and specific tobacco product use, all of which might have health implications.

CONCLUSIONS
This study represents the most comprehensive nationwide analysis of smoking prevalence and cessation behaviors to date in China.Its significance lies in its potential to inform public health initiatives and policy-making in China.By identifying specific subgroups with high smoking rates and low cessation, this research offers a strategic framework for tailored prevention and cessation initiatives.Additionally, this study deepens our understanding of the association between various risk factors and smoking intensity measured in pack-years.These insights significantly enrich our understanding of smoking dynamics in China, paving the way for targeted, data-driven methods to reduce smoking prevalence and improve health outcomes across diverse population groups.

Figure 2 .
Figure 2. Standardized prevalence of smoking and smoking cessation for population aged 40 years and above (%); A and B: smoking rate by sex and residence; C and D: smoking cessation rate by sex and residence

Table 2 .
Standardized prevalence of smoking and smoking cessation in Chinese adult population, 2021 (N=525048)

Table 3 .
Geographical variation in the prevalence of smoking and cessation in the Chinese adult population, 2021 (N=525048)

Table 5 .
Subgroup analysis of risk factors and pack-years* for current smokers in the Chinese adult population, 2021 (N=67730) *Reference category: 1-20 pack-years: Males (N=31927), Females (N=2722), <60 years (N=128321), ≥60 years (N=16328).AOR: adjusted odds ratio.AORs (95% CIs) were calculated using a multivariate logistic regression model.The age-specific model was adjusted for gender, residence, income level, education level, and geographical region of residence.The gender-specific model was adjusted for age, residence, income level, education level, and geographical region of residence.The significance of each predictor was assessed using the Wald chi-squared test, and p-values were derived accordingly.TIA: transient ischemic attack.

Table 4 .
Association between risk factors and pack-years* for current smokers in the Chinese adult population, 2021(N=67730) Reference category: 1-20 pack-years (N=34649).AOR: adjusted odds ratio.AORs (95% CIs) were calculated using a multivariate logistic regression model, adjusted for age, gender, residence, income level, education level, and geographical region of residence.The significance of each predictor was assessed using the Wald chi-squared test, and p-values were derived accordingly.TIA: transient ischemic attack. *